Mathematical modeling for evolution of heterogeneous modules in the brain

DOI10.1016/j.neunet.2014.07.013zbMath1368.92039OpenAlexW2052007127WikidataQ38239950 ScholiaQ38239950MaRDI QIDQ889351

Ichiro Tsuda, Yutaka Yamaguti

Publication date: 6 November 2015

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2014.07.013

zbMATH Keywords

evolutionsymmetry breakingmodularitytransfer entropyinformation flowcoupled-oscillator

Mathematics Subject Classification ID

Neural biology (92C20)

Related Items (3)

Understanding principles of integration and segregation using whole-brain computational connectomics: implications for neuropsychiatric disorders ⋮ Rutting prediction and analysis of influence factors based on multivariate transfer entropy and graph neural networks ⋮ Spike signal transmission between modules and the predictability of spike activity in modular neuronal networks

Cites Work

• Chemical oscillations, waves, and turbulence
• Information transfer in continuous processes
• Recurrent Infomax Generates Cell Assemblies, Neuronal Avalanches, and Simple Cell-Like Selectivity
• Calculation of information flow rate from mutual information
• Complex Systems: Chaos and Beyond
• Map model for synchronization of systems of many coupled oscillators
• Investigating Causal Relations by Econometric Models and Cross-spectral Methods
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Mathematical modeling for evolution of heterogeneous modules in the brain